Introduction

상위수준 그림 함수

상위수준 그림 함수의 주요 인자 (arguments)

  • main : 제목
  • xlab/ylab : x축 및 y축 레이블
  • xlim/ylim : x축 및 y축 범위
  • col : 색깔
  • lty : 선 모양
  • pch : 점 모양
  • cex : 그림 성분의 크기
  • lwd : 선 굵기
  • type : 그림 타입
dta <- read.csv("PK.csv")
head(dta)
##   ID TIME AMT    DV MDV
## 1  1 0.00   0  0.00   0
## 2  1 0.00   4  0.00   1
## 3  1 0.33   0  9.40   0
## 4  1 0.66   0 13.71   0
## 5  1 1.00   0 16.52   0
## 6  1 1.50   0 29.36   0
str(dta)
## 'data.frame':    456 obs. of  5 variables:
##  $ ID  : num  1 1 1 1 1 1 1 1 1 1 ...
##  $ TIME: num  0 0 0.33 0.66 1 1.5 2 3 4 6 ...
##  $ AMT : num  0 4 0 0 0 0 0 0 0 0 ...
##  $ DV  : num  0 0 9.4 13.7 16.5 ...
##  $ MDV : num  0 1 0 0 0 0 0 0 0 0 ...

scatter plot

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0])

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], log="y")
## Warning in xy.coords(x, y, xlabel, ylabel, log): 86 y values <= 0 omitted
## from logarithmic plot

plot(dta$TIME[dta$MDV==0], log(dta$DV[dta$MDV==0]))

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0]
     , xlab="Time (hr)", ylab="Concentration (ng/mL)" 
     , type="o", pch=2, col=1, main="PK time-course of Drug X"
     , xlim =c(-2,218), ylim=c(0,80))

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], axes=F,
     , xlab="Time (hr)", ylab="Concentration (ng/mL)" 
     , type="o", pch=2, col=1, main="PK time-course of Drug X"
     , xlim =c(-2,218), ylim=c(0,80))
axis(1, at=seq(0, 218, 24))
axis(2)
box()

Histogram

d.demog <- read.csv("DEMOG.csv")

hist(d.demog$HT)

hist(d.demog$HT, breaks=10)
hist(d.demog$HT, nclass=10)

with density line

hist (d.demog$HT, probability=TRUE, breaks=10)
lines(density(d.demog$HT))

hist (d.demog$HT, probability=TRUE, breaks=9, xaxt="n"
      , main="Histogram for Height", xlab="Height (cm)", ylab="Probability (%)")
axis(1, at=seq(min(d.demog$HT), max(d.demog$HT), 3))
lines(density(d.demog$HT))

hist (d.demog$HT, probability=TRUE, breaks=9, xaxt="n"
      , main="Histogram for Height", xlab="Height (cm)", ylab="Probability (%)"
      , col = "lightblue", border = "pink")
axis(1, at=seq(min(d.demog$HT), max(d.demog$HT), 3))
lines(density(d.demog$HT))

Box-Whisker Plot

boxplot(d.demog$WT)

boxplot(d.demog$WT ~ d.demog$SEX)

boxplot(split(d.demog$WT, d.demog$SEX))

boxplot(WT ~ SEX, data=d.demog)

boxplot(d.demog$WT ~ d.demog$SEX
        , names=c("Male","Female"), ylab="AGE, year", ylim=c(min(d.demog$WT)-2, max(d.demog$WT)+2)
        , col="pink")

boxplot(d.demog$WT ~ d.demog$SEX
        , names=c("Male","Female"), ylab="AGE, year", ylim=c(min(d.demog$WT)-2, max(d.demog$WT)+2)
        , col=c("lightblue", "salmon"), width=c(0.6, 1))

-varwidth: if varwidth is TRUE, the boxes are drawn with widths proportional to the square-roots of the number of observations in the groups.

boxplot(d.demog$WT ~ d.demog$SEX
        , names=c("Male","Female"), ylab="AGE, year", ylim=c(min(d.demog$WT)-2, max(d.demog$WT)+2)
        , col=c("lightblue", "salmon")
        , varwidth=TRUE)

Bar Plot

barplot(d.demog$HT)

VADeaths
##       Rural Male Rural Female Urban Male Urban Female
## 50-54       11.7          8.7       15.4          8.4
## 55-59       18.1         11.7       24.3         13.6
## 60-64       26.9         20.3       37.0         19.3
## 65-69       41.0         30.9       54.6         35.1
## 70-74       66.0         54.3       71.1         50.0
barplot(VADeaths, border = "dark blue")

barplot(VADeaths, col = rainbow(20))

barplot(VADeaths, col = heat.colors(8))

barplot(VADeaths, col = gray.colors(4))

barplot(VADeaths, col = gray.colors(4), log="x")

barplot(VADeaths, col = gray.colors(4), log="y")

barplot(VADeaths, col = gray.colors(4), log="xy")

pie chart

drug.X.market <- c(0.12, 0.29, 0.32, 0.22, 0.11, 0.28)
names(drug.X.market) <- c("South Korea","China","USA","Japan","Austria","EU")
pie(drug.X.market)

matplot 함수

matrix와 column 사이의 그림

pct.95 <- read.csv("pct95.csv")
matplot(pct.95[,1], pct.95[,2:ncol(pct.95)], pch=1)

matplot(pct.95[,1], pct.95[,2:ncol(pct.95)], pch=1, col=c(1,2,1), type="l", lty=1, lwd=c(1,2,1))

Scatter plot matrices (pairs plots)

pairs(d.demog)

add a loess smoother, type

pairs(d.demog, panel = panel.smooth)

panel.cor <- function(x, y, digits=2, prefix="", cex.cor)
{
    usr <- par("usr"); on.exit(par(usr))
    par(usr = c(0, 1, 0, 1))
    r = (cor(x, y))
    txt <- format(c(r, 0.123456789), digits=digits)[1]
    txt <- paste(prefix, txt, sep="")
    if(missing(cex.cor)) cex <- 1.5
    text(0.5, 0.5, txt, cex = 1.5)
}

pairs(d.demog, lower.panel=panel.smooth, upper.panel=panel.cor)

하위수준 그림 함수

점, 선, 설명 추가 하기

plot(pct.95$TIME, pct.95$PCT50, main="PK of Drug X"
     , type="l", xlab="Time (h)", ylab="Concentration (ng/ml)"
     , ylim=range(0,80), lty=1, col="red", lwd=2)

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], main="PK of Drug X"
     , type="n", xlab="Time (h)", ylab="Concentration (ng/ml)"
     , ylim=range(0,80))
points(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], pch = 16, cex=0.8)
lines(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], col="black", lwd=1)
abline(40, 0, col="red", lty=2)                               # abline(a,b): y=a+b*x
legend("topright", legend=c("Individual concentrations")
       , lty=1, col="black")

polygon 함수

plot(c(1, 10), c(1, 6), type = "n")
polygon(c(2,8,8,2), c(5,4,3,2), col="lightgreen")

plot(c(1, 9), 1:2, type = "n")
polygon(1:9, c(2,1,2,1,1,2,1,2,1),
        col = c("red", "blue"),
        border = c("green", "yellow"),
        lwd = 3, lty = c("dashed", "solid"))

그림 출력하기

pdf graphics devices

pdf("PK_of_Drug_X.pdf")

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], main="PK of Drug X"
     , type="n", xlab="Time (h)", ylab="Concentration (ng/ml)"
     , ylim=range(0,80))
points(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], pch = 16, cex=0.8)
lines(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], col="black", lwd=1)
abline(40, 0, col="red", lty=2)                               #abline(a,b): y=a+b*x
legend("topright", legend=c("Individual concentrations")
       , lty=1, col="black")

dev.off()
## quartz_off_screen 
##                 2

PNG graphics devices

png("PK_of_Drug_X.png")

plot(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], main="PK of Drug X"
     , type="n", xlab="Time (h)", ylab="Concentration (ng/ml)"
     , ylim=range(0,80))
points(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], pch = 16, cex=0.8)
lines(dta$TIME[dta$MDV==0], dta$DV[dta$MDV==0], col="black", lwd=1)
abline(40, 0, col="red", lty=2)                               #abline(a,b): y=a+b*x
legend("topright", legend=c("Individual concentrations")
       , lty=1, col="black")

dev.off()
## quartz_off_screen 
##                 2